IBM SPSS Neural Networks offers non-linear data modeling procedures that enable you to discover more complex relationships in your data. Using the procedures in IBM SPSS Neural Networks, you can develop more accurate and effective predictive models.

A computational neural network is a set of non-linear data modeling tools consisting of input and output layers plus one or two hidden layers. The connections between neurons in each layer have associated weights, which are iteratively adjusted by the training algorithm to minimize error and provide accurate predictions.

The procedures in IBM SPSS Neural Networks complement the more traditional statistics in IBM SPSS Statistics Base and its modules. Find associations in your data with Neural Networks and then confirm their significance with traditional statistical techniques.

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